Abstract
This analysis generates tables and figures related to the characteristics of the virtual assistants included in the eligible papers. It is a collaborative research activity as part of the IDEAIS project.
library(here)
library(tidyverse)
library(kableExtra)
library(DT)
library(stringr)
library(grid)
library(gridExtra)
library(ggforce) # for parallel sets diagram
library(gghighlight)
# just in case
set.seed(nchar("IDEAIS - scoping review paper"))
FALSE Using ',' as decimal and '.' as grouping mark. Use read_delim() for more control.
The following tables and figures are the results of the analysis of the characteristics of the virtual assistants.
FALSE Saving 14 x 14 in image
Tables below show the numbers and percentages used in Section 3 of the paper. They are not shown as tables per se but as pieces of information intertwined in the narrative.
Temporal distribution of virtual assistants according to their development status (av_status)
| Development stage of virtual assisstants | N | % |
|---|---|---|
| Design | 2 | 5% |
| Requirements and design | 4 | 11% |
| Implementation | 5 | 14% |
| Prototype | 26 | 70% |
| id | av_name |
|---|---|
| 001 | SpaceBook |
| 040 | Paval |
| 044 | NA |
| 049 | Loki |
| 053 | TreasureHuntBot |
What are the most used platforms?
| av_platform | n |
|---|---|
| NA | 19 |
| Robot | 3 |
| Cortana | 2 |
| Telegram | 2 |
| Agent | 1 |
| Alexa | 1 |
| Ambro | 1 |
| Atrv-jr mobile robot | 1 |
| Google assistant | 1 |
| Kinect | 1 |
| Kiosk | 1 |
| Line | 1 |
| Microsoft hololens | 1 |
| Satnav | 1 |
| Teamtalk | 1 |
Out of 37 papers, the implementated platform is mentioned in 14 studies, which is about 38%.
How many virtual assisstants are named?
| id | av_name | year | av_app_norm | av_application |
|---|---|---|---|---|
| 001 | SpaceBook | 2018 | Tourism | Turismo |
| 011 | CitiCafe | 2018 | Recommendation | Citizen support for the solution of civic problems in the city |
| 015 | MIRob | 2018 | Healthcare | Assistance robot for the elderly and disabled |
| 016 | PeopleBot | 2019 | Healthcare | Assistance robot for the elderly and disabled |
| 035 | CAGA | 2013 | Education | Conversational interface for the use and access of geospatial functions |
| 040 | Paval | 2019 | Tourism | Pois recommendation |
| 045 | TITERIA | 2017 | Tourism; Cultural heritage | Smart tourist information points with travel information organized in ontologies |
| 047 | Trip 4 All | 2015 | Tourism | Tourism |
| 049 | Loki | 2019 | Recommendation | Chatbot with location recognition |
| 053 | TreasureHuntBot | 2018 | Education; Entertainment | Chatbot for multiplayer game |
| 056 | SatNav | 2019 | Navigation | Driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. |
| 101 | Diana | 2019 | Disaster management | Disaster management (floods) |
Number of named virtual assisstants 32% (12/37)
av_arch) and development status (av_status)FALSE Saving 12 x 8 in image
| G | App domain | Geo goal | Ref - Year | App desc | Geo desc | Research areas |
|---|---|---|---|---|---|---|
| 1 | Disaster management | Mapping | [101] 2019 | Disaster management (floods) | Georeferenced maps with layers of relevant information | Fuzzy search algorithms, Knowledge graphs |
| Education | Spatial operators by concepts | [035] 2013 | Conversational interface for the use and access of geospatial functions | Spatial data analysis | Conversational agent | |
| Mapping | [010] 2018 | Education (in communicative competencies) in construction environments | Space-time Immersion in a BIM environment | Bim environments, Conversational agent, Game engines | ||
| Healthcare | Positioning | [058] 2016 | Health | Monitoring of health parameters in patients through their location | Cloud, Iot | |
| (Object) positioning | [015] 2018 | Assistance robot for the elderly and disabled | Identifying spatial relationships between objects within an environment | Assistive robotics, Human-robot interaction, Speech recognition, Uncertain term interpretation | ||
| Navigation | [027] 2018 | Outside navigation for blind pedestrians | Outdoor navigation | Conversational agent | ||
| (Object) positioning | [016] 2019 | Assistance robot for the elderly and disabled | Search for objects based on the recognition of their characteristics within an indoor environment | Assistive robotics, Human-robot interaction, Speech recognition, Uncertain term interpretation | ||
| Recommendation | Positioning | [037] 2010 | Customization of services depending on the position and user data (e.g., check-in at an airport) | Indoor positioning and navigation | Conversational agent, Multi-agent system | |
| Positioning | [044] 2017 | Information consultation and recovery | Treatment of queries with location information of POIs (bussines) | Artificial intelligence | ||
| Mapping | [011] 2018 | Citizen support for the solution of civic problems in the city | Presentation of relevant information and registration of complaints in specific locations | Continuous learning, Conversational agent, Crowd sourcing, Intent classifier, Natural language processing, Proactive interaction | ||
| Positioning | [038] 2019 | Get local information from conversational agents embedded in a local neighborhood, complemented with navigation | Outdoor positioning | Conversational agent, Multi-agent system | ||
| Positioning | [007] 2019 | Restaurant recommendation | Outdoor positioning | Recommender systems, Similarity algorithms | ||
| Proximity | [008] 2019 | Information search system in digital libraries | Localization of digital resources in digital libraries through geospatial queries | Knowledge graphs, Linked open data, Natural language processing | ||
| Summarisation | [020] 2019 | Weather narration for blind people | Data access to meteorological data | Natural language processing | ||
| Place recognition | [049] 2019 | Chatbot with location recognition | Chat panel with a map viewer for access to geospatial information | Government open data, Knowledge graph, Linked data, Location-aware chatbots, Semantic enrichment | ||
| Tourism | Question answering | [018] 2012 | Tourism | Navigation based on questions-answers | Speech recognition, Text-to-speech responses | |
| Mapping | [047] 2015 | Tourism | Multimedia and personalized experience about places visited | Gamification, Natural language processing | ||
| (Object) positioning | [024] 2018 | Guided tours | Identification of the object that the user looks at; 3D reconstruction of heritage buildings; data access | Semantic annotation, Speech recognition | ||
| Navigation | [001] 2018 | Turismo | Visibility of places of interest from the point of view of the tourist (pedestrian); route guide; outdoor navigation | Speech recognition, Text-to-speech responses | ||
| (Object) positioning | [021] 2019 | Guided tours | Identification of the object that the user looks at | Conversational agent, Mixed reality, Speech recognition | ||
| Positioning | [040] 2019 | Pois recommendation | Estimation of the need for information and possible geographical references expressed by users | Artificial intelligence, Knowledge graphs, Natural language processing, Ontologies, Semantic queries | ||
| Positioning | [012] 2019 | Outdoor navigation for touristic guides | Outdoor navigation, route planning and place guides | Artificial intelligence, Natural language processing | ||
| Tourism; Cultural heritage | Navigation | [057] 2011 | Tours in archeological sites | A tour to a set of exhibits located within a cultural heritage site by means of an avatar | Augmented reality, Automata, Rfid | |
| Positioning | [045] 2017 | Smart tourist information points with travel information organized in ontologies | Regions of interest organize knowledge base, POI location | Affective computing, Animation engine, Embodied conversational agents, Ontologies, Speech recognition | ||
| 2 | Conversation | Navigation | [050] 2019 | Conversational interface between a human operator and a team of one or more robots | Detection and recovery of human-robot communication | Human–robot communication, Language grounding, Physically situated dialogue, Spoken-dialogue systems |
| Question answering | [041] 2020 | In situ conversational search and assistance system | Structural patterns of questions related to places and their human-generated responses using the MS MARCO V2.1 data set | Named entity recognition, Question answering | ||
| Education; Entertainment | Positioning | [054] 2015 | Gamified mobile guide applications | Efficiency improvement for gamification-based location | Embodied conversational agents, Gamification | |
| Mapping | [053] 2018 | Chatbot for multiplayer game | Promote code-literacy through a multiplayer game | Code literacy, Messaging bot, Mixed reality | ||
| Linguistic | Place recognition | [048] 2017 | Automatic speech recognition for place entities | Recognition of words that define places in dialects and regions of interest organized in a knowledge base | Entity relation, Knowledge graphs, Speech recognition | |
| Reasoning on spatial relations | [026] 2018 | Recognition of spatial relationships in text | Establishment of spatial relationships between objects in a scene | Machine learning, Natural language processing | ||
| Place recognition | [043] 2018 | Conversational system for indian languages | Identification and classification of words that denote places or location | Linear models, Named entity recognition, Neural network | ||
| Place recognition | [046] 2018 | Automatic text recognition for place entities | Recognition of places in unstructured text | Deep learning, Entity relation, Named entity recognition, Neural machine translation | ||
| Navigation | Space modelling | [025] 2010 | Evaluation of routes generated by a robot (indoor maps) | Indoor space modeling | Modeling of indoor spaces, Natural language description of indoor spaces | |
| Positioning | [039] 2011 | Conversational learning agent | Navigation through complex and challenging space environments | Conversational agent | ||
| Positioning | [004] 2019 | Indoor navigation | Indoor positioning and navigation | Natural language processing | ||
| Positioning | [056] 2019 | Driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. | Route selection | Natural language interfaces, Vehicle navigation systems | ||
| Tourism; Entertainment | Positioning | [014] 2018 | Education, tourism, entertainment | Physical location of objects and solving puzzles | Conversational agent, Deep-linking, Natural language processing |
FALSE label_key: av_areas
FALSE Saving 10 x 8 in image
| Others: research areas cited once |
|---|
| Affective computing |
| Animation engine |
| Augmented reality |
| Automata |
| Bim environments |
| Cloud |
| Code literacy |
| Continuous learning |
| Crowd sourcing |
| Deep-linking |
| Deep learning |
| Fuzzy search algorithms |
| Game engines |
| Government open data |
| Human–robot communication |
| Intent classifier |
| Iot |
| Knowledge graph |
| Language grounding |
| Linear models |
| Linked data |
| Linked open data |
| Location-aware chatbots |
| Machine learning |
| Messaging bot |
| Modeling of indoor spaces |
| Natural language description of indoor spaces |
| Natural language interfaces |
| Neural machine translation |
| Neural network |
| Physically situated dialogue |
| Proactive interaction |
| Question answering |
| Recommender systems |
| Rfid |
| Semantic annotation |
| Semantic enrichment |
| Semantic queries |
| Similarity algorithms |
| Spoken-dialogue systems |
| Vehicle navigation systems |
## - Session info ---------------------------------------------------------------
## setting value
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## os Windows 10 x64
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## language (EN)
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## ctype Spanish_Spain.1252
## tz Europe/Paris
## date 2020-08-31
##
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##
## P -- Loaded and on-disk path mismatch.